• ETRI Journal
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• 제37권5호
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• pp.1023-1031
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• 2015

In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

• 한국컴퓨터정보학회논문지
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• 제17권12호
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• pp.83-93
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• 2012

본 논문에서는 기존의 퍼지 클러스터링 기반 이미지 분할의 성능과 계산 효율을 개선하기 위해 퍼지 클러스터링의 목적 함수를 수정하는 이미지 분할 프레임워크를 제안한다. 제안하는 이미지 분할 프레임워크는 주변 픽셀들에 가중치를 부여함으로써 현재 센터 픽셀 연산을 위해 주변 픽셀들의 중요성을 고려하는 지역 가중치 적용 퍼지 클러스터링 기법을 포함한다. 이러한 가중치들은 각 멤버쉽들의 중요성을 표시하기 위해 현재 픽셀과 대응되는 각 주변 픽셀들 사이의 거리차에 의해 결정되어 지며, 이러한 프로세서는 향상된 클러스터링 성능을 보장한다. 제안하는 방법의 성능을 평가하기 위해 분할 계수, 분할 엔트로피, Xie-Bdni 함수, Fukuyzma-Sugeno 함수와 같은 네 가지 클러스터 유효성 함수를 이용하여 분석하였다. 모의실험 결과, 제안한 방법은 기존의 다른 퍼지 클러스터링 기법들보다 클러스터 유효성 함수들뿐만 아니라 분할과 조밀도 측면에서 우수한 성능을 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.563-565
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• 1998

In this paper, we are proposed optimization method of fuzzy model in order to complex and nonlinear system. In the fuzzy modeling, a premise identification is very important to describe the charateristics of a given unknown system. Then, the proposed fuzzy model implements system structure and parameter identification, using the fuzzy inference method and genetic algorithms. Inference method for fuzzy model presented in our paper include the simplified inference and linear inference. Time series data for gas furance and sewage treatment process are used to evaluate the performance of the proposed model. Also, the performance index with weighted value is proposed to achieve a balance between the results of performance for the training and testing data.

• 한국전기전자재료학회논문지
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• 제29권1호
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• pp.58-61
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• 2016

Degradation in power cables used in distribution lines to the material of the wire, manufacturing method, but also the line of the environment, generates a variety of degradation depending upon the type of load. The local wire deterioration weighted wire breakage accident can occur frequently, causing significant proprietary damage can lead to accidents and precious. In this study, the signal detected by the eddy current aim to develop algorithms capable of determining the signals for the top part and at least part of the signal by using a signal processing technique called K-means algorithm.

• 산업경영시스템학회지
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• 제38권3호
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.

• 전기학회논문지
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• 제62권4호
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• pp.554-561
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• 2013

In this paper, we introduce a modeling and a process simulator developed with the aid of pRBFNNs for activated sludge process in the sewage treatment system. Activated sludge process(ASP) of sewage treatment system facilities is a process that handles biological treatment reaction and is a very complex system with non-linear characteristics. In this paper, we carry out modeling by using essential ASP factors such as water effluent quality, the manipulated value of various pumps, and water inflow quality, and so on. Intelligent algorithms used for constructing process simulator are developed by considering multi-output polynomial radial basis function Neural Networks(pRBFNNs) as well as Fuzzy C-Means clustering and Particle Swarm Optimization. Here, the apexes of the antecedent gaussian functions of fuzzy rules are decided by C-means clustering algorithm and the apexes of the consequent part of fuzzy rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The coefficients of the consequent polynomial of fuzzy rules and performance index are considered by the Least Square Estimation and Mean Squared Error. The descriptions of developed process simulator architecture and ensuing operation method are handled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4336-4354
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• 2018

Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.

• 유통과학연구
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• 제15권7호
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• pp.35-41
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• 2017

Purpose - A product bundling is a marketing approach where multiple products or components are packaged together into one bundle solution. This paper aims to introduce an optimal bundle search problem (hereinafter called "OBSP") which may be embedded with online recommendation system to provide an optimized service considering pairwise discount and delivery cost. Research design, data, and methodology - Online retailers have their own discount policy and it is time consuming for online shoppers to find an optimal bundle. Unlike an online system recommending one item for each search, the OBSP considers multiple items for each search. We propose a mathematical formulation with numerical example for the OBSP and analyzed the complexity of the problem. Results - We provide two results from the complexity analysis. In general case, the OBSP belongs to strongly NP-Hard which means the difficulty of the problem while the special case of OBSP can be solved within polynomial time by transforming the OBSP into the minimum weighted perfect matching problem. Conclusions - In this paper, we propose the OBSP to provide a customized service considering bundling price and delivery cost. The results of research will be embedded with an online recommendation system to help customers for easy and smart online shopping.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.796-801
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• 1994

Measuring noise, sound quality or acoustical comfort presents a difficult task for the acoustic engineer. Sound and noise are ultimately jugded by human beings acting as analysers. Regulations for determining noise levels are based on A-weighted SPL measurement performed with only one microphone. This method of measurement is usually specified when determining whether the ear can be physically damaged. Such a simple measurement procedure is not able to determine annoyance of sound events or sound quality in general. For some years investigations with binaural measurement analysis technique have shown new possibilities for the objective determination of sound quality. By using Artificial Head technology /1/, /2/ in conjunction with psychoacoustic evaluation algorithms - and taking into account binaural signal processing of human hearing, considerable progress regarding the analysis of sounds has been made. Because sound events often arise in a complex way, direct conclusions about components subjectively judged to be annoying with regard to their causes and transmission paths, can be drawn in a limited way only. A new procedure, complementing binaural measurement technology combined with mulit-channel measuements of acceleration sensor signals has been developed. This involves correlating signals influencing sound quality, analyzed by means of human hearing, with signals form different acceleration sensors fixed at different positions of the sound source. Now it is possible to recognize the source and the transmission way of those signals which have an influence on the annoyance of sound.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권12호
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• pp.471-480
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• 2016

최근 국가 기반 시스템, 국방 및 안보 시스템 등에 대한 사이버 공격의 피해 규모가 점차 커지고 있으며, 군에서도 사이버전에 대한 중요성을 인식하고 전 평시 구분 없이 대비하고 있다. 이에 네트워크 보안에서 탐지와 대응에 핵심적인 역할을 하는 침입 탐지 시스템의 중요성이 증대되고 있다. 침입 탐지 시스템은 탐지 방법에 따라 오용 탐지, 이상 탐지 방식으로 나뉘는데, 근래에는 두 가지 방식을 혼합 적용한 하이브리드 침입 탐지 방식에 대한 연구가 진행 중이다. 그렇지만 기존 연구들은 높은 계산량이 요구된다는 점에서 근 실시간 네트워크 환경에 부적합하다는 문제점이 있었다. 본 논문에서는 기존의 하이브리드 침입 탐지 시스템의 성능 문제를 보완할 수 있는 효과적인 속성 선택 기법을 적용한 의사 결정 트리와 가중 K-평균 알고리즘 기반의 고성능 하이브리드 침입 탐지 시스템을 제안하였다. 상호 정보량과 유전자 알고리즘 기반의 속성 선택 기법을 적용하여 침입을 더 빠르고 효율적으로 탐지할 수 있으며, 오용 탐지 모델과 이상 탐지 모델을 위계적으로 결합하여 구조적으로 고도화된 하이브리드 침입 탐지 시스템을 제안하였다. 실험을 통해 제안한 하이브리드 침입 탐지 시스템은 98.68%로 높은 탐지율을 보장함과 동시에, 속성 선택 기법을 적용하여 고성능 침입 탐지를 수행할 수 있음을 검증하였다.